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The study of cycloaddition mechanisms is central to the fabrication of extended sp2 carbon nanostructures. Reaction modeling in this context has focused mostly on putative, energetically preferred, exothermic products with limited consideration for symmetry allowed or forbidden mechanistic effects. Here, we introduce a scheme for classifying symmetry-forbidden reaction coordinates in Woodward-Hoffmann correlation diagrams. Topological classifiers grant access to the study of reaction pathways and correlation diagrams in the same footing, for the purpose of elucidating mechanisms and products of polycyclic aromatic azomethine ylide (PAMY) cycloadditions with pentacene-yielding polycyclic aromatic hydrocarbons with an isoindole core in the solid-state and on surfaces as characterized by mass spectrometry and scanning tunneling microscopy, respectively. By means of a tight-binding reaction model and density functional theory (DFT) we find topologically-allowed pathways if a product is endothermic, and topologically-forbidden if a product is exothermic. Our work unveils topological classification as a crucial element for reaction modeling for nanographene engineering, and highlights its fundamental role in the design of cycloadditions in on-surface and solid-state chemical reactions, while underscoring that exothermic pathways can be topologically-forbidden.

Calculating perturbation response properties of materials from first principles provides a vital link between theory and experiment, but is bottlenecked by the high computational cost. Here a general framework is proposed to perform density functional perturbation theory (DFPT) calculations by neural networks, greatly improving the computational efficiency. Automatic differentiation is applied on neural networks, facilitating accurate computation of derivatives. High efficiency and good accuracy of the approach are demonstrated by studying electron-phonon coupling and related physical quantities. This work brings deep-learning density functional theory and DFPT into a unified framework, creating opportunities for developing ab initio artificial intelligence.

Phonons have provided an ideal platform for a variety of intriguing physical states, such as non-Abelian braiding and the Haldane model. It is promising that phonons will realize the complicated nodal states accompanying unusual quantum phenomena. Here, we propose the hybrid nodal surface and nodal line (NS+NL) phonons beyond the single-genre nodal phonons. We categorize the NS+NL phonons into two- and four-band situations based on symmetry analysis and compatibility relationships. Combining database screening with first-principles calculations, we identify the ideal candidate materials for realizing all categorized NS+NL phonons. Our calculations and tight-binding models further demonstrate that the interplay between NS and NL induces unique phenomena. In space group (SG) 113, the quadratic NL acts as a hub of the Berry curvature between two NSs, generating ribbonlike surface states (SSs). In SG 128, the NS serves as the counterpart of the Weyl NL, in which NS-NL mixed topological SSs are observed. Our findings extend the scope of hybrid nodal states and enrich the phononic states in realistic materials., Comment: 27+35 pages, 5+44 figures, 1+3 tables